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Are you looking to enhance your Python- Beginner to Advance skills? If yes, then you have come to the right place. Our comprehensive course on Python- Beginner to Advance will assist you in producing the best possible outcome by mastering the Python- Beginner to Advance skills. The Python- Beginner to Advance course is for those who want to be successful. In the Python- Beginner to Advance course, you will learn the essential knowledge needed to become well versed in Python- Beginner to Advance. Our course starts with the basics of Python- Beginner to Advance and gradually progresses towards advanced topics. Therefore, each lesson of this Python- Beginner to Advance course is intuitive and easy to understand. Why would you choose the Python- Beginner to Advance course from Compliance Central: Lifetime access to Python- Beginner to Advance course materials Full tutor support is available from Monday to Friday with the Python- Beginner to Advance course Learn Python- Beginner to Advance skills at your own pace from the comfort of your home Gain a complete understanding of Python- Beginner to Advance course Accessible, informative Python- Beginner to Advance learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Python- Beginner to Advance course Study Python- Beginner to Advance in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Python- Beginner to Advance course Curriculum Breakdown of the Python- Beginner to Advance Course Introduction Curriculum Overview What's New command line basics python installation Pycham-ce ide installation Setting up environment Running python code git and github overview Python Data Types Python Arithmetic Operators Numbers Variable Assignments Strings Introduction Indexing and Slicing with Strings String Properties and Methods CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Python- Beginner to Advance course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Python- Beginner to Advance. It is also great for professionals who are already working in Python- Beginner to Advance and want to get promoted at work. Requirements To enrol in this Python- Beginner to Advance course, all you need is a basic understanding of the English Language and an internet connection. Career path The Python- Beginner to Advance course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors. Python Developer: £35,000 to £70,000 per year Data Analyst: £25,000 to £55,000 per year Machine Learning Engineer: £45,000 to £85,000 per year Software Engineer: £40,000 to £75,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

Who is this course for? Enscape Rendering Training Course. The Enscape Rendering Training Course is tailored for architects, interior designers, and design students aiming to learn realistic visualizations using Enscape. Whether you prefer 1-on-1 in-person or online courses, this training is best for you. Click here for more info: Website Training duration: 5 hrs Method: 1-on-1 and Tailored content Schedule: Customize your training. Choose any hour from Mon to Sat, 9 am to 7 pm Call 02077202581 or WhatsApp at 07970325184 to book. Course Outline: Enscape Rendering Software Training (5 hours) Course 1: Enscape for Revit Hour 1: 1. Introduction to Enscape: Overview of Enscape rendering software, its features, and benefits. 2. Installing and Setting up Enscape: Step-by-step guidance on installing and configuring Enscape for Revit. 3. Enscape Interface: Familiarizing with the Enscape user interface and navigation controls within Revit. Hour 2: 4. Enscape Materials: Exploring material creation, application, and customization within Enscape for Revit. 5. Lighting in Enscape: Understanding different lighting options, adjusting light settings, and creating realistic lighting effects. Hour 3: 6. Enscape Camera Settings: Manipulating camera angles, perspectives, and settings for optimal visualization. 7. Enscape Rendering Settings: Exploring various rendering settings and techniques to enhance the quality of the final output. Hour 4: 8. Enscape Rendering Workflow: Demonstrating a step-by-step workflow for generating renderings and walkthroughs using Enscape in Revit. 9. Advanced Features: Introduction to advanced features such as creating panoramas, virtual reality (VR) walkthroughs, and creating animations in Enscape. Hour 5: 10. Tips and Tricks: Sharing tips and techniques for maximizing efficiency and achieving high-quality results in Enscape for Revit. 11. Q&A and Troubleshooting: Addressing participant questions, providing troubleshooting guidance, and discussing common challenges and solutions. OR Course Outline: Enscape Rendering Software Training (5 hours) Course 1: Enscape for Sketchup Hour 1: 1. Introduction to Enscape: Overview of Enscape rendering software, its features, and benefits for SketchUp users. 2. Installing and Setting up Enscape: Step-by-step guidance on installing and configuring Enscape for SketchUp. 3. Enscape Interface: Familiarizing with the Enscape user interface and navigation controls within SketchUp. Hour 2: 4. Enscape Materials: Exploring material creation, application, and customization within Enscape for SketchUp. 5. Lighting in Enscape: Understanding different lighting options, adjusting light settings, and creating realistic lighting effects. Hour 3: 6. Enscape Camera Settings: Manipulating camera angles, perspectives, and settings for optimal visualization in SketchUp. 7. Enscape Rendering Settings: Exploring various rendering settings and techniques to enhance the quality of the final output. Hour 4: 8. Enscape Rendering Workflow: Demonstrating a step-by-step workflow for generating renderings and walkthroughs using Enscape in SketchUp. 9. Advanced Features: Introduction to advanced features such as creating panoramas, virtual reality (VR) walkthroughs, and creating animations in Enscape. Hour 5: 10. Tips and Tricks: Sharing tips and techniques for maximizing efficiency and achieving high-quality results in Enscape for SketchUp. 11. Q&A and Troubleshooting: Addressing participant questions, providing troubleshooting guidance, and discussing common challenges and solutions. Learning Outcome: After completing the Enscape (VR) Training and Interactive Workshop, participants will master real-time walkthroughs, set up VR applications, efficiently migrate models, navigate designs dynamically, update objects in real-time, control visual styles, adjust day-time settings, export and share designs, utilize the asset library, and gain a comprehensive overview of Enscape. These skills will enable them to confidently visualize and display 3D designs without cloud uploads or external software, enhancing communication and collaboration in architectural projects. What does the Enscape Training & Interactive Workshop offer? The Enscape Training & Interactive Workshop is designed to help you get up and running with Virtual Reality (VR) in a cost-effective manner. It covers hardware and software setup, navigation techniques, real-time updates, material settings, and more. The workshop also allows participants to experience VR firsthand. What are the benefits of attending the Enscape (VR) Training and Interactive Workshop? By attending this workshop, you will gain the ability to perform real-time walkthroughs of your designs in 3D. You can view your projects in VR without the need for cloud uploads or exporting to other 3D software. The workshop offers extensive asset libraries, collaboration, and annotation sharing, enhancing your design visualization capabilities. What are the prerequisites for attending the Enscape (VR) Training and Interactive Workshop? No prior knowledge of Enscape is required. However, assistance from IT management may be necessary for hardware and software installation. Logistics, such as room suitability and technical requirements, will be discussed before the workshop. What will I learn in the Enscape (VR) Training and Interactive Workshop? The workshop covers hardware setup, software installation, and configuration. You will learn how to migrate models from Revit and SketchUp into VR, navigate through designs, update objects and materials in real-time, and utilize various visual styles and settings. The course also includes interactive workshops with support from our expert tutors. Enscape rendering courses offer valuable benefits: Real-time Visualization: Instantly visualize designs for quick iterations and informed decisions. Seamless Integration: Streamline rendering by integrating with popular design software. High-Quality Visuals: Create photorealistic presentations and walkthroughs. Efficient Design Communication: Enhance collaboration and communication during presentations. Enhanced Design Iteration: Explore options and make informed decisions in real-time. Time and Cost Savings: Reduce rendering time and deliver projects more efficiently. Portfolio Enhancement: Elevate your portfolio with visually striking renderings, opening new opportunities.

The course 'Deep Learning & Neural Networks Python - Keras' provides a comprehensive introduction to deep learning using the Keras library in Python. It covers topics ranging from basic neural networks to more advanced concepts, such as convolutional neural networks, image augmentation, and performance improvement techniques for various datasets. Learning Outcomes: Understand the fundamental concepts of deep learning and how it differs from traditional machine learning. Gain proficiency in using Keras, a powerful deep learning library, for building and training neural network models. Develop practical skills in creating and optimizing neural network models for different datasets, including image recognition tasks and regression problems. Why buy this Deep Learning & Neural Networks Python - Keras? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Deep Learning & Neural Networks Python - Keras there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Deep Learning & Neural Networks Python - Keras course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Deep Learning & Neural Networks Python - Keras does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning & Neural Networks Python - Keras was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Deep Learning & Neural Networks Python - Keras is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

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Overview This comprehensive course on Computer Vision: C++ and OpenCV with GPU support will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Computer Vision: C++ and OpenCV with GPU support comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Computer Vision: C++ and OpenCV with GPU support. It is available to all students, of all academic backgrounds. Requirements Our Computer Vision: C++ and OpenCV with GPU support is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 5 sections • 22 lectures • 02:31:00 total length •Module 01: Driver installation: 00:06:00 •Module 02: Cuda toolkit installation: 00:01:00 •Module 03: Compile OpenCV from source with CUDA support part-1: 00:06:00 •Module 04: Compile OpenCV from source with CUDA support part-2: 00:05:00 •Module 05: Python environment for flownet2-pytorch: 00:09:00 •Module 01: Read camera & files in a folder (C++): 00:11:00 •Module 02: Edge detection (C++): 00:08:00 •Module 03: Color transformations (C++): 00:07:00 •Module 04: Using a trackbar (C++): 00:06:00 •Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++): 00:13:00 •Module 01: Background segmentation with MOG (C++): 00:04:00 •Module 02: MOG and MOG2 cuda implementation (C++ - CUDA): 00:03:00 •Module 03: Special app: Track class: 00:06:00 •Module 04: Special app: Track bgseg Foreground objects: 00:08:00 •Module 01: A simple application to prepare dataset for object detection (C++): 00:08:00 •Module 02: Train model with openCV ML module (C++ and CUDA): 00:13:00 •Module 03: Object detection with openCV ML module (C++ CUDA): 00:06:00 •Module 01: Optical flow with Farneback (C++): 00:08:00 •Module 02: Optical flow with Farneback (C++ CUDA): 00:06:00 •Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA): 00:05:00 •Module 04: Optical flow with Nvidia Flownet2 (Python): 00:05:00 •Module 05: Performance Comparison: 00:07:00

This course begins with a comprehensive introduction to RFID technology, focusing on both low and high-frequency cards. You'll explore the Proxmark3 RDV4 device, a powerful RFID testing tool, learning its installation and implementation to understand how RFID systems can be ethically analysed and tested.

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Duration 5 Days 30 CPD hours This course is intended for This course is intended for Experienced system administrators responsible for deploying and administering JBoss Enterprise Application Platform 6 in large-scale production environments. At least 2 years' experience as a JBoss Enterprise Application Platform administrator. Be a Red Hat Certified Specialist in Enterprise Application Server Administration on Enterprise Application Platform 6 (or later) or have equivalent experience . Overview Upon successful completion of this course, students will be able to provision and manage Red Hat JBoss Enterprise Application Platform 6 in large-scale production environments. This course empowers you to provision and manage Red Hat© JBoss© Enterprise Application Platform (JBoss EAP) in large-scale production environments. Intended for experienced administrators, this course will help you gain a deeper understanding of how to work with JBoss EAP by taking a closer look at installation, clustering, deployments, scripting, management, messaging, and security with a view towards building on the skills established in the Red Hat JBoss Application Administration I (JB248) course. 1 - INSTALLATION Given the proper installation media, perform Red Hat© JBoss© Enterprise Application Platform 6 installations that are repeatable, upgradeable, and silent. 2 - CLUSTERING Demonstrate a proficient knowledge of clustering components, their configuration, and application to clustered architectures. 3 - DEPLOYMENT Deploy an application in various types of production environments. 4 - SCRIPTING Script various configuration and management scenarios using command line interface (CLI). 5 - MANAGEMENT Use various tools to monitor and manage JBoss Enterprise Application Platform. 6 - MESSAGING Learn how to manage supported messaging systems. 7 - SECURITY Configure security settings that include authentication, authorization, networking, and the management interfaces. 8 - OVERVIEW OF JBOSS OPERATIONS NETWORK Learn the functionality of JBoss Operations Network and its use cases. Also learn how to install a JBoss Operations Network server, an agent, and agent plug-ins. 9 - MONITORING RESOURCES Learn how to use JBoss Operations Network to monitor managed resources, including defining alerts, baselines, and notifications Additional course details: Nexus Humans Red Hat JBoss Application Administration II (AD348) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Red Hat JBoss Application Administration II (AD348) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.